Comparative Mental Time Travel: Is There a Cognitive Divide between Humans and Animals in Episodic Memory and Planning?
Bibliographic record
Abstract
Abstract Mental time travel is defined as the human ability to remember unique personal past experiences (episodic memory) and to anticipate and plan future events. Considerable debate has arisen around the question of whether nonhuman animals are also capable of mental time travel, ranging from complete denial of the ability in nonhumans to the suggestion that they have episodic memory and readily plan for the future. We evaluate the current evidence available from comparative cognition experiments and human-developmental research. Studies of episodic-like memory in birds and nonhuman mammals have centered on their ability to remember what, where, and when a single event occurred. Although clear evidence for memory of what and where has been shown, memory of when does not always appear and may depend on both the species tested and the experimental design used. We argue for a clear distinction between remembering when in absolute time an event occurred and remembering how long ago it occurred. Studies of neural processes indicate that the hippocampus is necessary for episodic memory in humans and episodic-like memory in rats. It is argued that studies of nonhumans should not focus on presence versus absence of human traits but should examine alternative mental time travel abilities in animals that may have evolved independently as adaptations to a particular ecological niche.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".